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Fast algorithm for constructing neighbor-joining phylogenetic trees

机译:构造邻居连接系统树的快速算法

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To improve the performance of Saitou and Nei's algorithm (SN) and Studier and Keppler's improved algorithm (SK) for constructing neighbor-joining phylogenetic trees and reduce the time complexity of the computation, a fast algorithm is proposed. The proposed algorithm includes three techniques. First, a linear array A[N] is introduced to store the sum of every row of the distance matrix (the same as SK), which can eliminate many repeated computations. Secondly, the value of A[i] is computed only once at the beginning of the algorithm, and is updated by three elements in the iteration. Thirdly, a very compact formula for the sum of all the branch lengths of operational taxonomic units (OTUs) i and j is designed, and the correctness of the formula is proved. The experimental results show that the proposed algorithm is from tens to hundreds times faster than SN and roughly two times faster than SK when N increases, constructing a tree with 2 000 OTUs in 3 min on a current desktop computer. To earn the time with the cost of the space and reduce the computations in the innermost loop are the basic solutions for algorithms with many loops.
机译:为了提高Saitou和Nei算法(SN)以及Studier和Keppler改进算法(SK)的性能,以构造邻居加入的系统树并减少计算的时​​间复杂度,提出了一种快速算法。所提出的算法包括三种技术。首先,引入线性数组A [N]来存储距离矩阵每一行的和(与SK相同),这可以消除许多重复的计算。其次,A [i]的值在算法开始时仅计算一次,并在迭代中由三个元素更新。第三,设计了一个非常紧凑的公式,用于计算操作分类单元(OTU)i和j的所有分支长度之和,并证明了该公式的正确性。实验结果表明,所提出的算法比SN快数十到数百倍,而当N增加时,比SK快大约两倍。在当前的台式计算机上,用3分钟的时间构建了具有2000 OTU的树。以空间为代价来节省时间并减少最内层循环中的计算量是具有多个循环的算法的基本解决方案。

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